These plots indicate common QC properties like distribution of 1) number of reads per cell, 2) number of genes per cell, 3) fraction of reads mapping to mitochondrial genes detected per cell (higher fraction suggests cell disruption), 4) fraction of reads mapping to top 50 expressed genes, 5) and correlation between read depth and number of genes identified per cell.
## [1] "Number of genes Number of cells"
## [1] 17047 8186
## [1] "Number of genes Number of cells"
## [1] 17047 7138
## [1] "Number of variable genes"
## [1] 1199
List of genes whose expresion shows high correlaton with different top PCs are shown. One should be careful if a PC shows high expression with housekeeping genes (e.g. ribosomal/mitochondiral) experssion.
## [1] "correlation of PC values with nUMI and nGene"
## nGene nUMI
## nGene 1.0000 0.95000
## nUMI 0.9500 1.00000
## PC1 -0.0930 0.00270
## PC2 -0.0330 -0.00057
## PC3 -0.0570 -0.00088
## PC4 -0.0400 -0.00210
## PC5 0.0170 0.00450
## PC6 0.0290 -0.00570
## PC7 0.0300 0.00240
## PC8 0.0380 0.01200
## PC9 0.0260 0.00160
## PC10 -0.0210 0.00310
## PC11 -0.0050 0.00110
## PC12 0.0860 0.02700
## PC13 -0.0480 -0.00140
## PC14 0.0220 0.00280
## PC15 -0.0046 -0.00400
## PC16 -0.0470 -0.00062
## PC17 0.0014 0.00610
## PC18 0.0035 0.00099
## PC19 0.0063 0.00520
## PC20 -0.0070 -0.00820
PC Elbow plot can be used to identify most informtive PCs to be used for t-SNE analyses.
## [1] "Number of cells in different clusters:"
## CD4_TT_E_Memory Naive_T 3 TT_E_Memory
## 1888 986 827 795
## 5 NKT_exhausted B Macro
## 758 733 813 252
## 11
## 86
## [1] "Following marker genes were used for cluster labelling"